A/B testing is a randomized experiment with two variants, A and B. Such experiments are commonly used in web development, email marketing, and advertising design. In web development case, you define a control or original page (page A) and an experiment or variation (page B) of the original page to test against. The goal of the test is to randomly expose your web traffic to the different versions of a page to determine which version will result in a better defined goal such as higher conversion rates, longer duration periods, lower bounce rate, and so on. The statistics behind A/B testing can be Z-test, t-test, or Chi-square test.
Google Analytics offers an easy to use tool (content experiment) for conducting A/B testing. The process of setting up an A/B testing in Google Analytics is kind of straightforward.
(1) In Google Analytics, go to Behavior-> Experiments
(2) Choose an experiment objective: this can be bounce rate, duration time, and conversion.
(3) Configure your experiment: set up the url for your original page and your experiment page.
(4) Paste the experiment code immediately after the opening head tag at the top of your original page. Also make sure both of your original page and experiment page contain Google Anlytics track code.
(5) Check and start the experiment.